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1# Copyright 2021 Huawei Technologies Co., Ltd
2#
3# Licensed under the Apache License, Version 2.0 (the "License");
4# you may not use this file except in compliance with the License.
5# You may obtain a copy of the License at
6#
7# http://www.apache.org/licenses/LICENSE-2.0
8#
9# Unless required by applicable law or agreed to in writing, software
10# distributed under the License is distributed on an "AS IS" BASIS,
11# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
12# See the License for the specific language governing permissions and
13# limitations under the License.
14# ============================================================================
15import numpy as np
16import pytest
17import mindspore.context as context
18import mindspore.nn as nn
19from mindspore import Tensor
20from mindspore.ops import operations as P
21from mindspore.ops.composite import GradOperation
22
23context.set_context(mode=context.GRAPH_MODE, device_target="Ascend")
24
25dtype = np.float16
26x0 = Tensor(np.random.randn(3, 4, 3, 3, 3).astype(dtype))
27x1 = Tensor(np.random.randn(3, 4, 3, 3, 3).astype(dtype))
28
29
30class Net(nn.Cell):
31    def __init__(self, keep_prob):
32        super(Net, self).__init__()
33        self.drop = P.Dropout3D(keep_prob=keep_prob)
34
35    def construct(self, x):
36        return self.drop(x)
37
38
39class Grad(nn.Cell):
40    def __init__(self, network):
41        super(Grad, self).__init__()
42        self.grad = GradOperation(get_all=True, sens_param=True)
43        self.network = network
44        self.network.set_train()
45
46    def construct(self, x, y):
47        return self.grad(self.network)(x, y)
48
49
50@pytest.mark.level0
51@pytest.mark.env_onecard
52@pytest.mark.platform_arm_ascend_training
53@pytest.mark.platform_x86_ascend_training
54@pytest.mark.parametrize("context_mode", [context.GRAPH_MODE, context.PYNATIVE_MODE])
55def test_net_float32(context_mode):
56    """
57    Feature: aicpu ops Dropout3D.
58    Description: test Dropout3D forward.
59    Expectation: expect correct result.
60    """
61    context.set_context(mode=context_mode, device_target="Ascend")
62    net = Net(0.7)
63    output, mask = net(x0)
64    print(x0)
65    print(output)
66
67    y = (output.asnumpy() == (x0.asnumpy()/0.7).astype(dtype)).reshape(3*4, 3*3*3)
68    output_reshape = output.asnumpy().reshape(3*4, 3*3*3)
69    for i in range(3*4):
70        if not y[i].all():
71            assert output_reshape[i].sum() == 0
72    return output, mask
73
74
75@pytest.mark.level0
76@pytest.mark.env_onecard
77@pytest.mark.platform_arm_ascend_training
78@pytest.mark.platform_x86_ascend_training
79@pytest.mark.parametrize("context_mode", [context.GRAPH_MODE, context.PYNATIVE_MODE])
80def test_net_grad(context_mode):
81    """
82    Feature: aicpu ops Dropout3D.
83    Description: test Dropout3D backward.
84    Expectation: expect correct result.
85    """
86    net = Grad(Net(0.7))
87    y = test_net_float32(context_mode)
88    output = net(x1, y)
89    print("input: ", x1)
90    print("forward output: ", y)
91    print("backward output: ", output)
92